Probability distributions, and more generally positive measures, are central in fields as diverse as physics (to model the state density in quantum mechanics [1]}), in chemistry (to model the electron density of a molecule [2]}), in biology (to count occurrences of a gene expression in cells [3]}) or economics (to represent wealth distribution [4]}).
They are also of utmost importance to represent and manipulate data in Machine Learning (ML) [5]}, [6]}.
In most cases, measures are represented and approximated using either discrete distributions (such as point clouds and histograms) or continuous models (such as parameterized densities).
See Figure REF  for an example of a distribution discretized using these representations.
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